1. Field of the Invention
This invention relates generally to wireless communication systems. More particularly, it relates to a wireless communication system using a plurality of antenna elements with weighting and combining techniques for optimizing antenna diversity and combining gain for use in a system that uses spread spectrum.
2. Description of the Related Art
FIG. 1 shows a prior art adaptive array 10. Adaptive array 10 comprises multi-element antenna 12 where the received signals are weighted and combined to produce output signal 14. There are M antenna elements, with weights W1 to WM.
Antenna weights are typically generated to improve the performance of the output signal. For example, the received signals may be combined to maximize the output signal-to-noise ratio (SNR) or the output signal-to-interference-plus-noise ratio (SINR).
FIG. 2 shows a prior art adaptive array with weight generation, where the weights are generated in weight generation module 17 from output signal 14 and each of received signals 16.
One method for generating antenna weights is maximal ratio combining (MRC), where the weights are generated to maximize the desired signal SNR. A simple implementation technique to generate weights that are similar to MRC is Granlund combining, where the output signal is correlated with the complex conjugate of the received signal at each antenna for the weights for the corresponding antenna. This technique is described in “Wireless Communication System using a Plurality of Antenna Elements with Adaptive Weighting and Combining Techniques,” U.S. patent application Ser. No. 10/732,003, filed Dec. 10, 2003, hereby incorporated by reference into this application. This technique has the advantage that it is blind (does not require demodulation of the signal).
Spread spectrum is a method that can be used to suppress interference and distinguish desired and interfering signals. With spread spectrum, the desired signal (containing data at a given data rate) is multiplied by a higher rate pseudorandom sequence, which spreads the spectrum of the desired signal. The ratio of the bandwidth of the original desired signal (data bandwidth) to the spread spectrum signal is the spreading ratio. At the receiver, the spread spectrum signal is mixed with the spreading sequence and low pass filtered. The output is then the original desired signal, whereas any interfering signal is distorted and suppressed by the spreading ratio in the output signal.
Spread spectrum can be used as a method to distinguish the desired signal from interference in an adaptive array. One such technique is described in, “Spread Spectrum in a Four-Phase Communication System Employing Adaptive Antennas,” IEEE Trans. on Communications Special Issue on Spread-Spectrum Communications, May 1982 and in Spread-Spectrum Communications, IEEE Press, NY, 1983. In this technique, the output signal is despread, filtered, and respread, resulting in a signal, used as a reference signal, that has the desired signal unchanged, but any interference without the correct spreading sequence is distorted. This reference signal can be used with the standard least mean squares (LMS) algorithm: The reference signal is subtracted from the output signal, and this signal is used as an error signal to drive the weights to minimize the mean square error (MMSE) in the output signal. This MMSE algorithm thereby generates weights that maximize the output SINR, i.e., suppress interference and increase desired signal power. These MMSE weights also minimize the bit error rate of the output signal without consideration of the reduction in interference due to despreading.
However, it has been found that any technique that maximizes SINR must do so at the expense of reducing the SNR of the desired signal. In a spread spectrum system, any interference in the output is suppressed by the spreading ratio of the spread spectrum code. Therefore, although it is desirable to distinguish the desired signal from interference when generating the weights, maximizing output SINR may not be desirable as it may result in a reduction in the output SNR over MRC in order to achieve unneeded interference suppression. Therefore, it is desirable to provide a technique for weight generation in a spread spectrum system that maximizes the SNR of the desired signal only.